{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# operator, functools, itertools, toolz, fn, funcy 模块"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## operator 模块"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import operator as op"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`operator` 模块提供了各种操作符（`+,*,[]`）的函数版本方便使用："
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "加法："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "45\n"
     ]
    }
   ],
   "source": [
    "print reduce(op.add, range(10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "乘法："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "362880\n"
     ]
    }
   ],
   "source": [
    "print reduce(op.mul, range(1,10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`[]`："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[('a', 1), ('bb', 4), ('ccc', 2), ('dddd', 3)]\n",
      "[('a', 1), ('ccc', 2), ('dddd', 3), ('bb', 4)]\n",
      "[('a', 1), ('bb', 4), ('ccc', 2), ('dddd', 3)]\n"
     ]
    }
   ],
   "source": [
    "my_list = [('a', 1), ('bb', 4), ('ccc', 2), ('dddd', 3)]\n",
    "\n",
    "# 标准排序\n",
    "print sorted(my_list)\n",
    "\n",
    "# 使用元素的第二个元素排序\n",
    "print sorted(my_list, key=op.itemgetter(1))\n",
    "\n",
    "# 使用第一个元素的长度进行排序：\n",
    "print sorted(my_list, key=lambda x: len(x[0]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## functools 模块"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`functools` 包含很多跟函数相关的工具，比如之前看到的 `wraps` 函数，不过最常用的是 `partial` 函数，这个函数允许我们使用一个函数中生成一个新函数，这个函数使用原来的函数，不过某些参数被指定了："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10\n",
      "24\n"
     ]
    }
   ],
   "source": [
    "from functools import partial\n",
    "\n",
    "# 将 reduce 的第一个参数指定为加法，得到的是类似求和的函数\n",
    "sum_ = partial(reduce, op.add)\n",
    "\n",
    "# 将 reduce 的第一个参数指定为乘法，得到的是类似求连乘的函数\n",
    "prod_ = partial(reduce, op.mul)\n",
    "\n",
    "print sum_([1,2,3,4])\n",
    "print prod_([1,2,3,4])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`partial` 函数还可以按照键值对传入固定参数。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## itertools 模块"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`itertools` 包含很多与迭代器对象相关的工具，其中比较常用的是排列组合生成器 `permutations` 和 `combinations`，还有在数据分析中常用的 `groupby` 生成器："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from itertools import cycle, groupby, islice, permutations, combinations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`cycle` 返回一个无限的迭代器，按照顺序重复输出输入迭代器中的内容，`islice` 则返回一个迭代器中的一段内容："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['a', 'b', 'c', 'd', 'a', 'b', 'c', 'd', 'a', 'b']\n"
     ]
    }
   ],
   "source": [
    "print list(islice(cycle('abcd'), 0, 10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`groupby` 返回一个字典，按照指定的 `key` 对一组数据进行分组，字典的键是 `key`，值是一个迭代器： "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3 ['pig', 'cow', 'dog', 'cat']\n",
      "4 ['lion']\n",
      "5 ['hippo', 'tiger']\n",
      "7 ['giraffe']\n",
      "8 ['elephant']\n",
      "\n"
     ]
    }
   ],
   "source": [
    "animals = sorted(['pig', 'cow', 'giraffe', 'elephant',\n",
    "                  'dog', 'cat', 'hippo', 'lion', 'tiger'], key=len)\n",
    "\n",
    "# 按照长度进行分组\n",
    "for k, g in groupby(animals, key=len):\n",
    "    print k, list(g)\n",
    "print"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "排列："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['abc', 'acb', 'bac', 'bca', 'cab', 'cba']\n"
     ]
    }
   ],
   "source": [
    "print [''.join(p) for p in permutations('abc')]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "组合："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1, 2], [1, 3], [1, 4], [2, 3], [2, 4], [3, 4]]\n"
     ]
    }
   ],
   "source": [
    "print [list(c) for c in combinations([1,2,3,4], r=2)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## toolz, fn 和 funcy 模块"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "这三个模块的作用是方便我们在编程的时候使用函数式编程的风格。"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
